{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Getting started with `cartopy`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cartopy\n",
    "import cartopy.crs as ccrs\n",
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1441511b0>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# use matplotlib's built-in transform support, same function calls\n",
    "fig = plt.figure(figsize=(10, 4))\n",
    "axm = fig.add_subplot(1, 1, 1, projection=ccrs.Robinson(central_longitude=300.))\n",
    "\n",
    "# set the extent to global\n",
    "axm.set_global()\n",
    "\n",
    "# add standard background map\n",
    "axm.stock_img()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Plotting a global contour map \n",
    "\n",
    "Load a dataset of dissolved oxygen concentration in the thermocline (400-600 m depth)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
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       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:             (lat: 180, nbounds: 2, lon: 360, depth: 102, time: 1)\n",
       "Coordinates:\n",
       "  * lat                 (lat) float32 -89.5 -88.5 -87.5 -86.5 ... 87.5 88.5 89.5\n",
       "  * lon                 (lon) float32 -179.5 -178.5 -177.5 ... 177.5 178.5 179.5\n",
       "  * depth               (depth) float32 0.0 5.0 10.0 ... 5.3e+03 5.4e+03 5.5e+03\n",
       "  * time                (time) float32 8.214e+03\n",
       "Dimensions without coordinates: nbounds\n",
       "Data variables:\n",
       "    crs                 int32 -2147483647\n",
       "    lat_bnds            (lat, nbounds) float32 -90.0 -89.0 -89.0 ... 89.0 90.0\n",
       "    lon_bnds            (lon, nbounds) float32 -180.0 -179.0 ... 179.0 180.0\n",
       "    depth_bnds          (depth, nbounds) float32 0.0 2.5 ... 5.45e+03 5.5e+03\n",
       "    climatology_bounds  (time, nbounds) float32 7.512e+03 8.928e+03\n",
       "    o_an                (time, depth, lat, lon) float32 ...\n",
       "    o_mn                (time, depth, lat, lon) float32 ...\n",
       "    o_dd                (time, depth, lat, lon) float64 ...\n",
       "    o_sd                (time, depth, lat, lon) float32 ...\n",
       "    o_se                (time, depth, lat, lon) float32 ...\n",
       "    o_oa                (time, depth, lat, lon) float32 ...\n",
       "    o_gp                (time, depth, lat, lon) float64 ...\n",
       "Attributes: (12/49)\n",
       "    Conventions:                     CF-1.6, ACDD-1.3\n",
       "    title:                           World Ocean Atlas 2018 : mole_concentrat...\n",
       "    summary:                         Climatological mean dissolved oxygen for...\n",
       "    references:                      Garcia, H. E., K. Weathers, C. R. Paver,...\n",
       "    institution:                     National Centers for Environmental Infor...\n",
       "    comment:                         global climatology as part of the World ...\n",
       "    ...                              ...\n",
       "    publisher_email:                 NCEI.info@noaa.gov\n",
       "    nodc_template_version:           NODC_NetCDF_Grid_Template_v2.0\n",
       "    license:                         These data are openly available to the p...\n",
       "    metadata_link:                   https://www.nodc.noaa.gov/OC5/woa18/\n",
       "    date_created:                    2019-07-29 \n",
       "    date_modified:                   2019-07-29 </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-abc3c0b2-5a90-487b-8923-65a97ca176ea' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-abc3c0b2-5a90-487b-8923-65a97ca176ea' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 180</li><li><span>nbounds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 360</li><li><span class='xr-has-index'>depth</span>: 102</li><li><span class='xr-has-index'>time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9dfcc933-3a60-4d1e-b0c7-79fda5a958f4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9dfcc933-3a60-4d1e-b0c7-79fda5a958f4' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-1818598e-0e7d-4964-a809-0855828d8cc9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1818598e-0e7d-4964-a809-0855828d8cc9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83fa791f-7c0f-432e-8c83-45f52cb90b4b' class='xr-var-data-in' type='checkbox'><label for='data-83fa791f-7c0f-432e-8c83-45f52cb90b4b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.5 -178.5 ... 178.5 179.5</div><input id='attrs-72f15f9d-4dbe-40c1-8774-ccf8bf68c394' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72f15f9d-4dbe-40c1-8774-ccf8bf68c394' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b5b166a-ed54-41c9-8e14-45b92ca43b25' class='xr-var-data-in' type='checkbox'><label for='data-4b5b166a-ed54-41c9-8e14-45b92ca43b25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-179.5, -178.5, -177.5, ...,  177.5,  178.5,  179.5], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>depth</span></div><div class='xr-var-dims'>(depth)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 5.0 10.0 ... 5.4e+03 5.5e+03</div><input id='attrs-24afb9d6-4c9a-4ba2-b570-0b7a4fbafc0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24afb9d6-4c9a-4ba2-b570-0b7a4fbafc0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d15b8336-d5ae-4abd-826b-7d2861594a60' class='xr-var-data-in' type='checkbox'><label for='data-d15b8336-d5ae-4abd-826b-7d2861594a60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>bounds :</span></dt><dd>depth_bnds</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([0.00e+00, 5.00e+00, 1.00e+01, 1.50e+01, 2.00e+01, 2.50e+01, 3.00e+01,\n",
       "       3.50e+01, 4.00e+01, 4.50e+01, 5.00e+01, 5.50e+01, 6.00e+01, 6.50e+01,\n",
       "       7.00e+01, 7.50e+01, 8.00e+01, 8.50e+01, 9.00e+01, 9.50e+01, 1.00e+02,\n",
       "       1.25e+02, 1.50e+02, 1.75e+02, 2.00e+02, 2.25e+02, 2.50e+02, 2.75e+02,\n",
       "       3.00e+02, 3.25e+02, 3.50e+02, 3.75e+02, 4.00e+02, 4.25e+02, 4.50e+02,\n",
       "       4.75e+02, 5.00e+02, 5.50e+02, 6.00e+02, 6.50e+02, 7.00e+02, 7.50e+02,\n",
       "       8.00e+02, 8.50e+02, 9.00e+02, 9.50e+02, 1.00e+03, 1.05e+03, 1.10e+03,\n",
       "       1.15e+03, 1.20e+03, 1.25e+03, 1.30e+03, 1.35e+03, 1.40e+03, 1.45e+03,\n",
       "       1.50e+03, 1.55e+03, 1.60e+03, 1.65e+03, 1.70e+03, 1.75e+03, 1.80e+03,\n",
       "       1.85e+03, 1.90e+03, 1.95e+03, 2.00e+03, 2.10e+03, 2.20e+03, 2.30e+03,\n",
       "       2.40e+03, 2.50e+03, 2.60e+03, 2.70e+03, 2.80e+03, 2.90e+03, 3.00e+03,\n",
       "       3.10e+03, 3.20e+03, 3.30e+03, 3.40e+03, 3.50e+03, 3.60e+03, 3.70e+03,\n",
       "       3.80e+03, 3.90e+03, 4.00e+03, 4.10e+03, 4.20e+03, 4.30e+03, 4.40e+03,\n",
       "       4.50e+03, 4.60e+03, 4.70e+03, 4.80e+03, 4.90e+03, 5.00e+03, 5.10e+03,\n",
       "       5.20e+03, 5.30e+03, 5.40e+03, 5.50e+03], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.214e+03</div><input id='attrs-8a226e21-10bc-4d3e-a80e-e0d6ba2af883' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a226e21-10bc-4d3e-a80e-e0d6ba2af883' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2bfcce9-da16-41c1-942f-9988d518430c' class='xr-var-data-in' type='checkbox'><label for='data-b2bfcce9-da16-41c1-942f-9988d518430c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>units :</span></dt><dd>months since 1900-01-01 00:00:00</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>climatology :</span></dt><dd>climatology_bounds</dd></dl></div><div class='xr-var-data'><pre>array([8214.], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4931453e-f850-4a57-afd6-656fa2d73a37' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4931453e-f850-4a57-afd6-656fa2d73a37' class='xr-section-summary' >Data variables: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4c3f821d-c55c-4199-a5e1-5dbed2bb486e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c3f821d-c55c-4199-a5e1-5dbed2bb486e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3a8da29-f0c6-4153-99eb-1554a2b72c83' class='xr-var-data-in' type='checkbox'><label for='data-e3a8da29-f0c6-4153-99eb-1554a2b72c83' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>epsg_code :</span></dt><dd>EPSG:4326</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>inverse_flattening :</span></dt><dd>298.25723</dd></dl></div><div class='xr-var-data'><pre>array(-2147483647, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, nbounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dda88dd6-5297-4280-92b7-a7d9cbf6e68b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dda88dd6-5297-4280-92b7-a7d9cbf6e68b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e096edbe-1330-44c9-8b80-add3e20ad213' class='xr-var-data-in' type='checkbox'><label for='data-e096edbe-1330-44c9-8b80-add3e20ad213' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>latitude bounds</dd></dl></div><div class='xr-var-data'><pre>array([[-90., -89.],\n",
       "       [-89., -88.],\n",
       "       [-88., -87.],\n",
       "       ...,\n",
       "       [ 87.,  88.],\n",
       "       [ 88.,  89.],\n",
       "       [ 89.,  90.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-80a0a855-44ec-44ab-b097-03407643e816' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80a0a855-44ec-44ab-b097-03407643e816' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28e81b0b-546c-4b31-96ba-d5945e1303af' class='xr-var-data-in' type='checkbox'><label for='data-28e81b0b-546c-4b31-96ba-d5945e1303af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>longitude bounds</dd></dl></div><div class='xr-var-data'><pre>array([[-180., -179.],\n",
       "       [-179., -178.],\n",
       "       [-178., -177.],\n",
       "       ...,\n",
       "       [ 177.,  178.],\n",
       "       [ 178.,  179.],\n",
       "       [ 179.,  180.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth_bnds</span></div><div class='xr-var-dims'>(depth, nbounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ccfc4eaf-2b34-4193-8fa9-2d3679926027' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccfc4eaf-2b34-4193-8fa9-2d3679926027' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73e81f0f-4e2b-4ca8-97e8-9d92ff88e1ac' class='xr-var-data-in' type='checkbox'><label for='data-73e81f0f-4e2b-4ca8-97e8-9d92ff88e1ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>depth bounds</dd></dl></div><div class='xr-var-data'><pre>array([[0.00e+00, 2.50e+00],\n",
       "       [2.50e+00, 7.50e+00],\n",
       "       [7.50e+00, 1.25e+01],\n",
       "       ...,\n",
       "       [5.25e+03, 5.35e+03],\n",
       "       [5.35e+03, 5.45e+03],\n",
       "       [5.45e+03, 5.50e+03]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>climatology_bounds</span></div><div class='xr-var-dims'>(time, nbounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9f062d0e-dedf-499d-9fa0-d381ec46a31c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f062d0e-dedf-499d-9fa0-d381ec46a31c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23ae0fb2-9e5d-4492-b0de-b53535303063' class='xr-var-data-in' type='checkbox'><label for='data-23ae0fb2-9e5d-4492-b0de-b53535303063' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>This variable defines the bounds of the climatological time period for each time</dd></dl></div><div class='xr-var-data'><pre>array([[7512., 8928.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_an</span></div><div class='xr-var-dims'>(time, depth, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3bb0bb70-7d52-4e48-acf7-b462d890e8fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bb0bb70-7d52-4e48-acf7-b462d890e8fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40dda4e4-dd87-47dc-878d-2493d87f9412' class='xr-var-data-in' type='checkbox'><label for='data-40dda4e4-dd87-47dc-878d-2493d87f9412' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mole_concentration_of_dissolved_molecular_oxygen_in_sea_water</dd><dt><span>long_name :</span></dt><dd>Objectively analyzed mean fields for mole_concentration_of_dissolved_molecular_oxygen_in_sea_water at standard depth levels.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: mean within years time: mean over years</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>micromoles_per_kilogram</dd></dl></div><div class='xr-var-data'><pre>[6609600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_mn</span></div><div class='xr-var-dims'>(time, depth, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ed2671db-59ac-4213-b540-2203a37c23ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed2671db-59ac-4213-b540-2203a37c23ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e78c056-a102-444a-912c-1a210d9d70bd' class='xr-var-data-in' type='checkbox'><label for='data-6e78c056-a102-444a-912c-1a210d9d70bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mole_concentration_of_dissolved_molecular_oxygen_in_sea_water</dd><dt><span>long_name :</span></dt><dd>Average of all unflagged interpolated values at each standard depth level for mole_concentration_of_dissolved_molecular_oxygen_in_sea_water in each grid-square which contain at least one measurement.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: mean within years time: mean over years</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>micromoles_per_kilogram</dd></dl></div><div class='xr-var-data'><pre>[6609600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_dd</span></div><div class='xr-var-dims'>(time, depth, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4b077c6b-c97c-4371-80ce-f5de68616c73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b077c6b-c97c-4371-80ce-f5de68616c73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5db906e6-5beb-4760-afbf-bd1bf4dbc72d' class='xr-var-data-in' type='checkbox'><label for='data-5db906e6-5beb-4760-afbf-bd1bf4dbc72d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mole_concentration_of_dissolved_molecular_oxygen_in_sea_water number_of_observations</dd><dt><span>long_name :</span></dt><dd>The number of observations of mole_concentration_of_dissolved_molecular_oxygen_in_sea_water in each grid-square at each standard depth level.</dd><dt><span>cell_methods :</span></dt><dd>area: sum depth: point time: sum</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[6609600 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_sd</span></div><div class='xr-var-dims'>(time, depth, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-62db79bf-6631-4f3b-be9d-73a548a4de85' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62db79bf-6631-4f3b-be9d-73a548a4de85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ec7db1f-8eea-4931-9fe3-94d0c6004343' class='xr-var-data-in' type='checkbox'><label for='data-4ec7db1f-8eea-4931-9fe3-94d0c6004343' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>The standard deviation about the statistical mean of mole_concentration_of_dissolved_molecular_oxygen_in_sea_water in each grid-square at each standard depth level.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: standard_deviation</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>micromoles_per_kilogram</dd></dl></div><div class='xr-var-data'><pre>[6609600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_se</span></div><div class='xr-var-dims'>(time, depth, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f361b0c6-9ab9-4387-a0c6-a9acc51ef82a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f361b0c6-9ab9-4387-a0c6-a9acc51ef82a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e677b737-c08a-4aa0-8324-4535a4adda10' class='xr-var-data-in' type='checkbox'><label for='data-e677b737-c08a-4aa0-8324-4535a4adda10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mole_concentration_of_dissolved_molecular_oxygen_in_sea_water standard_error</dd><dt><span>long_name :</span></dt><dd>The standard error about the statistical mean of mole_concentration_of_dissolved_molecular_oxygen_in_sea_water in each grid-square at each standard depth level.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>micromoles_per_kilogram</dd></dl></div><div class='xr-var-data'><pre>[6609600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_oa</span></div><div class='xr-var-dims'>(time, depth, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b2119bf3-c540-487d-8484-eb8636979dd3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2119bf3-c540-487d-8484-eb8636979dd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5931e0ae-38bf-47f5-bbbc-731012a02b99' class='xr-var-data-in' type='checkbox'><label for='data-5931e0ae-38bf-47f5-bbbc-731012a02b99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mole_concentration_of_dissolved_molecular_oxygen_in_sea_water</dd><dt><span>long_name :</span></dt><dd>statistical mean value minus the objectively analyzed mean value for mole_concentration_of_dissolved_molecular_oxygen_in_sea_water.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: mean with years time: mean over years</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>micromoles_per_kilogram</dd></dl></div><div class='xr-var-data'><pre>[6609600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_gp</span></div><div class='xr-var-dims'>(time, depth, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4575a2f8-118e-4ed1-afed-dfea6186ce8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4575a2f8-118e-4ed1-afed-dfea6186ce8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fad99d1d-63e3-4300-b10e-b86c68f404a8' class='xr-var-data-in' type='checkbox'><label for='data-fad99d1d-63e3-4300-b10e-b86c68f404a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>The number of grid-squares within the smallest radius of influence around each grid-square which contain a statistical mean for mole_concentration_of_dissolved_molecular_oxygen_in_sea_water.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: mean within years time: mean over years</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[6609600 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ea8d0257-af33-4dd0-8bb5-41667ea8a536' class='xr-section-summary-in' type='checkbox'  ><label for='section-ea8d0257-af33-4dd0-8bb5-41667ea8a536' class='xr-section-summary' >Attributes: <span>(49)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>title :</span></dt><dd>World Ocean Atlas 2018 : mole_concentration_of_dissolved_molecular_oxygen_in_sea_water Annual  1.00 degree</dd><dt><span>summary :</span></dt><dd>Climatological mean dissolved oxygen for the global ocean from in situ oceanographic profile data</dd><dt><span>references :</span></dt><dd>Garcia, H. E., K. Weathers, C. R. Paver, I. Smolyar, T. P. Boyer, R. A. Locarnini, M. M. Zweng, A. V. Mishonov, O. K. Baranova, D. Seidov, and J. R. Reagan, 2019. World Ocean Atlas 2018, Volume 3: Dissolved Oxygen, Apparent Oxygen Utilization, and Oxygen Saturation.  A. V. Mishonov, Technical Ed., NOAA Atlas NESDIS 83</dd><dt><span>institution :</span></dt><dd>National Centers for Environmental Information (NCEI)</dd><dt><span>comment :</span></dt><dd>global climatology as part of the World Ocean Atlas project</dd><dt><span>id :</span></dt><dd>woa18_all_o00_01.nc</dd><dt><span>naming_authority :</span></dt><dd>gov.noaa.ncei</dd><dt><span>sea_name :</span></dt><dd>World-Wide Distribution</dd><dt><span>time_coverage_start :</span></dt><dd>1900-01-01</dd><dt><span>time_coverage_end :</span></dt><dd>2017-12-31</dd><dt><span>time_coverage_duration :</span></dt><dd>P!!Y</dd><dt><span>time_coverage_resolution :</span></dt><dd>P01Y</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.0</dd><dt><span>geospatial_vertical_min :</span></dt><dd>0.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>5500.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>1.00 degrees</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>1.00 degrees</dd><dt><span>geospatial_vertical_units :</span></dt><dd>m</dd><dt><span>geospatial_vertical_resolution :</span></dt><dd>SPECIAL</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>down</dd><dt><span>creator_name :</span></dt><dd>Ocean Climate Laboratory</dd><dt><span>creator_email :</span></dt><dd>NCEI.info@noaa.gov</dd><dt><span>creator_url :</span></dt><dd>http://www.ncei.noaa.gov</dd><dt><span>creator_type :</span></dt><dd>group</dd><dt><span>creator_institution :</span></dt><dd>National Centers for Environmental Information</dd><dt><span>project :</span></dt><dd>World Ocean Atlas Project</dd><dt><span>processing_level :</span></dt><dd>processed</dd><dt><span>keywords :</span></dt><dd>Oceans&lt; Ocean Oxygen &gt; Dissolved Oxygen</dd><dt><span>keywords_vocabulary :</span></dt><dd>ISO 19115</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table v49</dd><dt><span>contributor_name :</span></dt><dd>Ocean Climate Laboratory</dd><dt><span>contributor_role :</span></dt><dd>Calculation of climatologies</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>publisher_name :</span></dt><dd>National Centers for Environmental Information (NCEI)</dd><dt><span>publisher_institution :</span></dt><dd>National Centers for Environmental Information</dd><dt><span>publisher_type :</span></dt><dd>institution</dd><dt><span>publisher_url :</span></dt><dd>http://www.ncei.noaa.gov/</dd><dt><span>publisher_email :</span></dt><dd>NCEI.info@noaa.gov</dd><dt><span>nodc_template_version :</span></dt><dd>NODC_NetCDF_Grid_Template_v2.0</dd><dt><span>license :</span></dt><dd>These data are openly available to the public. Please acknowledge the use of these data with the text given in the acknowledgment attribute.</dd><dt><span>metadata_link :</span></dt><dd>https://www.nodc.noaa.gov/OC5/woa18/</dd><dt><span>date_created :</span></dt><dd>2019-07-29 </dd><dt><span>date_modified :</span></dt><dd>2019-07-29 </dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:             (lat: 180, nbounds: 2, lon: 360, depth: 102, time: 1)\n",
       "Coordinates:\n",
       "  * lat                 (lat) float32 -89.5 -88.5 -87.5 -86.5 ... 87.5 88.5 89.5\n",
       "  * lon                 (lon) float32 -179.5 -178.5 -177.5 ... 177.5 178.5 179.5\n",
       "  * depth               (depth) float32 0.0 5.0 10.0 ... 5.3e+03 5.4e+03 5.5e+03\n",
       "  * time                (time) float32 8.214e+03\n",
       "Dimensions without coordinates: nbounds\n",
       "Data variables:\n",
       "    crs                 int32 ...\n",
       "    lat_bnds            (lat, nbounds) float32 ...\n",
       "    lon_bnds            (lon, nbounds) float32 ...\n",
       "    depth_bnds          (depth, nbounds) float32 ...\n",
       "    climatology_bounds  (time, nbounds) float32 ...\n",
       "    o_an                (time, depth, lat, lon) float32 ...\n",
       "    o_mn                (time, depth, lat, lon) float32 ...\n",
       "    o_dd                (time, depth, lat, lon) float64 ...\n",
       "    o_sd                (time, depth, lat, lon) float32 ...\n",
       "    o_se                (time, depth, lat, lon) float32 ...\n",
       "    o_oa                (time, depth, lat, lon) float32 ...\n",
       "    o_gp                (time, depth, lat, lon) float64 ...\n",
       "Attributes: (12/49)\n",
       "    Conventions:                     CF-1.6, ACDD-1.3\n",
       "    title:                           World Ocean Atlas 2018 : mole_concentrat...\n",
       "    summary:                         Climatological mean dissolved oxygen for...\n",
       "    references:                      Garcia, H. E., K. Weathers, C. R. Paver,...\n",
       "    institution:                     National Centers for Environmental Infor...\n",
       "    comment:                         global climatology as part of the World ...\n",
       "    ...                              ...\n",
       "    publisher_email:                 NCEI.info@noaa.gov\n",
       "    nodc_template_version:           NODC_NetCDF_Grid_Template_v2.0\n",
       "    license:                         These data are openly available to the p...\n",
       "    metadata_link:                   https://www.nodc.noaa.gov/OC5/woa18/\n",
       "    date_created:                    2019-07-29 \n",
       "    date_modified:                   2019-07-29 "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import xarray as xr\n",
    "ds = xr.open_dataset('woa18_all_o00_01.nc', decode_times=False)\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
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    {
     "data": {
      "text/plain": [
       "{'Conventions': 'CF-1.6, ACDD-1.3',\n",
       " 'title': 'World Ocean Atlas 2018 : mole_concentration_of_dissolved_molecular_oxygen_in_sea_water Annual  1.00 degree',\n",
       " 'summary': 'Climatological mean dissolved oxygen for the global ocean from in situ oceanographic profile data',\n",
       " 'references': 'Garcia, H. E., K. Weathers, C. R. Paver, I. Smolyar, T. P. Boyer, R. A. Locarnini, M. M. Zweng, A. V. Mishonov, O. K. Baranova, D. Seidov, and J. R. Reagan, 2019. World Ocean Atlas 2018, Volume 3: Dissolved Oxygen, Apparent Oxygen Utilization, and Oxygen Saturation.  A. V. Mishonov, Technical Ed., NOAA Atlas NESDIS 83',\n",
       " 'institution': 'National Centers for Environmental Information (NCEI)',\n",
       " 'comment': 'global climatology as part of the World Ocean Atlas project',\n",
       " 'id': 'woa18_all_o00_01.nc',\n",
       " 'naming_authority': 'gov.noaa.ncei',\n",
       " 'sea_name': 'World-Wide Distribution',\n",
       " 'time_coverage_start': '1900-01-01',\n",
       " 'time_coverage_end': '2017-12-31',\n",
       " 'time_coverage_duration': 'P!!Y',\n",
       " 'time_coverage_resolution': 'P01Y',\n",
       " 'geospatial_lat_min': -90.0,\n",
       " 'geospatial_lat_max': 90.0,\n",
       " 'geospatial_lon_min': -180.0,\n",
       " 'geospatial_lon_max': 180.0,\n",
       " 'geospatial_vertical_min': 0.0,\n",
       " 'geospatial_vertical_max': 5500.0,\n",
       " 'geospatial_lat_units': 'degrees_north',\n",
       " 'geospatial_lat_resolution': '1.00 degrees',\n",
       " 'geospatial_lon_units': 'degrees_east',\n",
       " 'geospatial_lon_resolution': '1.00 degrees',\n",
       " 'geospatial_vertical_units': 'm',\n",
       " 'geospatial_vertical_resolution': 'SPECIAL',\n",
       " 'geospatial_vertical_positive': 'down',\n",
       " 'creator_name': 'Ocean Climate Laboratory',\n",
       " 'creator_email': 'NCEI.info@noaa.gov',\n",
       " 'creator_url': 'http://www.ncei.noaa.gov',\n",
       " 'creator_type': 'group',\n",
       " 'creator_institution': 'National Centers for Environmental Information',\n",
       " 'project': 'World Ocean Atlas Project',\n",
       " 'processing_level': 'processed',\n",
       " 'keywords': 'Oceans< Ocean Oxygen > Dissolved Oxygen',\n",
       " 'keywords_vocabulary': 'ISO 19115',\n",
       " 'standard_name_vocabulary': 'CF Standard Name Table v49',\n",
       " 'contributor_name': 'Ocean Climate Laboratory',\n",
       " 'contributor_role': 'Calculation of climatologies',\n",
       " 'cdm_data_type': 'Grid',\n",
       " 'publisher_name': 'National Centers for Environmental Information (NCEI)',\n",
       " 'publisher_institution': 'National Centers for Environmental Information',\n",
       " 'publisher_type': 'institution',\n",
       " 'publisher_url': 'http://www.ncei.noaa.gov/',\n",
       " 'publisher_email': 'NCEI.info@noaa.gov',\n",
       " 'nodc_template_version': 'NODC_NetCDF_Grid_Template_v2.0',\n",
       " 'license': 'These data are openly available to the public. Please acknowledge the use of these data with the text given in the acknowledgment attribute.',\n",
       " 'metadata_link': 'https://www.nodc.noaa.gov/OC5/woa18/',\n",
       " 'date_created': '2019-07-29 ',\n",
       " 'date_modified': '2019-07-29 '}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.attrs"
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  {
   "cell_type": "code",
   "execution_count": 30,
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       "\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;o_an&#x27; (time: 1, depth: 102, lat: 180, lon: 360)&gt;\n",
       "[6609600 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 -89.5 -88.5 -87.5 -86.5 -85.5 ... 86.5 87.5 88.5 89.5\n",
       "  * lon      (lon) float32 -179.5 -178.5 -177.5 -176.5 ... 177.5 178.5 179.5\n",
       "  * depth    (depth) float32 0.0 5.0 10.0 15.0 ... 5.3e+03 5.4e+03 5.5e+03\n",
       "  * time     (time) float32 8.214e+03\n",
       "Attributes:\n",
       "    standard_name:  mole_concentration_of_dissolved_molecular_oxygen_in_sea_w...\n",
       "    long_name:      Objectively analyzed mean fields for mole_concentration_o...\n",
       "    cell_methods:   area: mean depth: mean time: mean within years time: mean...\n",
       "    grid_mapping:   crs\n",
       "    units:          micromoles_per_kilogram</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'o_an'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>depth</span>: 102</li><li><span class='xr-has-index'>lat</span>: 180</li><li><span class='xr-has-index'>lon</span>: 360</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3688c96a-a70c-4d7d-92d8-4bd429ae5fc4' class='xr-array-in' type='checkbox' checked><label for='section-3688c96a-a70c-4d7d-92d8-4bd429ae5fc4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[6609600 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-093df83e-98c2-41a3-8872-6039c968c964' class='xr-section-summary-in' type='checkbox'  checked><label for='section-093df83e-98c2-41a3-8872-6039c968c964' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-78f9fc23-b879-4aca-af36-4e1e764ca6f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78f9fc23-b879-4aca-af36-4e1e764ca6f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b042fbb-3b6a-4527-8cb2-129eaa2aaf4a' class='xr-var-data-in' type='checkbox'><label for='data-8b042fbb-3b6a-4527-8cb2-129eaa2aaf4a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.5 -178.5 ... 178.5 179.5</div><input id='attrs-7206df40-b5b2-4992-af65-90fd3c9cb88b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7206df40-b5b2-4992-af65-90fd3c9cb88b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4fe2d6f1-56da-426a-a6b5-160aeedd99fd' class='xr-var-data-in' type='checkbox'><label for='data-4fe2d6f1-56da-426a-a6b5-160aeedd99fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-179.5, -178.5, -177.5, ...,  177.5,  178.5,  179.5], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>depth</span></div><div class='xr-var-dims'>(depth)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 5.0 10.0 ... 5.4e+03 5.5e+03</div><input id='attrs-c6f3de03-c4f7-4b1d-ad40-4eaaffacfc65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c6f3de03-c4f7-4b1d-ad40-4eaaffacfc65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38d0e9c8-2cd0-46d2-b05f-df4868b3fc7d' class='xr-var-data-in' type='checkbox'><label for='data-38d0e9c8-2cd0-46d2-b05f-df4868b3fc7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>bounds :</span></dt><dd>depth_bnds</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([0.00e+00, 5.00e+00, 1.00e+01, 1.50e+01, 2.00e+01, 2.50e+01, 3.00e+01,\n",
       "       3.50e+01, 4.00e+01, 4.50e+01, 5.00e+01, 5.50e+01, 6.00e+01, 6.50e+01,\n",
       "       7.00e+01, 7.50e+01, 8.00e+01, 8.50e+01, 9.00e+01, 9.50e+01, 1.00e+02,\n",
       "       1.25e+02, 1.50e+02, 1.75e+02, 2.00e+02, 2.25e+02, 2.50e+02, 2.75e+02,\n",
       "       3.00e+02, 3.25e+02, 3.50e+02, 3.75e+02, 4.00e+02, 4.25e+02, 4.50e+02,\n",
       "       4.75e+02, 5.00e+02, 5.50e+02, 6.00e+02, 6.50e+02, 7.00e+02, 7.50e+02,\n",
       "       8.00e+02, 8.50e+02, 9.00e+02, 9.50e+02, 1.00e+03, 1.05e+03, 1.10e+03,\n",
       "       1.15e+03, 1.20e+03, 1.25e+03, 1.30e+03, 1.35e+03, 1.40e+03, 1.45e+03,\n",
       "       1.50e+03, 1.55e+03, 1.60e+03, 1.65e+03, 1.70e+03, 1.75e+03, 1.80e+03,\n",
       "       1.85e+03, 1.90e+03, 1.95e+03, 2.00e+03, 2.10e+03, 2.20e+03, 2.30e+03,\n",
       "       2.40e+03, 2.50e+03, 2.60e+03, 2.70e+03, 2.80e+03, 2.90e+03, 3.00e+03,\n",
       "       3.10e+03, 3.20e+03, 3.30e+03, 3.40e+03, 3.50e+03, 3.60e+03, 3.70e+03,\n",
       "       3.80e+03, 3.90e+03, 4.00e+03, 4.10e+03, 4.20e+03, 4.30e+03, 4.40e+03,\n",
       "       4.50e+03, 4.60e+03, 4.70e+03, 4.80e+03, 4.90e+03, 5.00e+03, 5.10e+03,\n",
       "       5.20e+03, 5.30e+03, 5.40e+03, 5.50e+03], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.214e+03</div><input id='attrs-3c1361c7-afba-4169-b588-0760a6499813' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c1361c7-afba-4169-b588-0760a6499813' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f2156df-e3f9-4a46-8157-90231101cd12' class='xr-var-data-in' type='checkbox'><label for='data-7f2156df-e3f9-4a46-8157-90231101cd12' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>units :</span></dt><dd>months since 1900-01-01 00:00:00</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>climatology :</span></dt><dd>climatology_bounds</dd></dl></div><div class='xr-var-data'><pre>array([8214.], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-725ab81f-1c8b-4403-b40c-27bb8b54f0cd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-725ab81f-1c8b-4403-b40c-27bb8b54f0cd' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mole_concentration_of_dissolved_molecular_oxygen_in_sea_water</dd><dt><span>long_name :</span></dt><dd>Objectively analyzed mean fields for mole_concentration_of_dissolved_molecular_oxygen_in_sea_water at standard depth levels.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: mean within years time: mean over years</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>micromoles_per_kilogram</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'o_an' (time: 1, depth: 102, lat: 180, lon: 360)>\n",
       "[6609600 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 -89.5 -88.5 -87.5 -86.5 -85.5 ... 86.5 87.5 88.5 89.5\n",
       "  * lon      (lon) float32 -179.5 -178.5 -177.5 -176.5 ... 177.5 178.5 179.5\n",
       "  * depth    (depth) float32 0.0 5.0 10.0 15.0 ... 5.3e+03 5.4e+03 5.5e+03\n",
       "  * time     (time) float32 8.214e+03\n",
       "Attributes:\n",
       "    standard_name:  mole_concentration_of_dissolved_molecular_oxygen_in_sea_w...\n",
       "    long_name:      Objectively analyzed mean fields for mole_concentration_o...\n",
       "    cell_methods:   area: mean depth: mean time: mean within years time: mean...\n",
       "    grid_mapping:   crs\n",
       "    units:          micromoles_per_kilogram"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#ds.keys()\n",
    "ds.o_an"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
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       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;depth&#x27; (depth: 102)&gt;\n",
       "array([0.00e+00, 5.00e+00, 1.00e+01, 1.50e+01, 2.00e+01, 2.50e+01, 3.00e+01,\n",
       "       3.50e+01, 4.00e+01, 4.50e+01, 5.00e+01, 5.50e+01, 6.00e+01, 6.50e+01,\n",
       "       7.00e+01, 7.50e+01, 8.00e+01, 8.50e+01, 9.00e+01, 9.50e+01, 1.00e+02,\n",
       "       1.25e+02, 1.50e+02, 1.75e+02, 2.00e+02, 2.25e+02, 2.50e+02, 2.75e+02,\n",
       "       3.00e+02, 3.25e+02, 3.50e+02, 3.75e+02, 4.00e+02, 4.25e+02, 4.50e+02,\n",
       "       4.75e+02, 5.00e+02, 5.50e+02, 6.00e+02, 6.50e+02, 7.00e+02, 7.50e+02,\n",
       "       8.00e+02, 8.50e+02, 9.00e+02, 9.50e+02, 1.00e+03, 1.05e+03, 1.10e+03,\n",
       "       1.15e+03, 1.20e+03, 1.25e+03, 1.30e+03, 1.35e+03, 1.40e+03, 1.45e+03,\n",
       "       1.50e+03, 1.55e+03, 1.60e+03, 1.65e+03, 1.70e+03, 1.75e+03, 1.80e+03,\n",
       "       1.85e+03, 1.90e+03, 1.95e+03, 2.00e+03, 2.10e+03, 2.20e+03, 2.30e+03,\n",
       "       2.40e+03, 2.50e+03, 2.60e+03, 2.70e+03, 2.80e+03, 2.90e+03, 3.00e+03,\n",
       "       3.10e+03, 3.20e+03, 3.30e+03, 3.40e+03, 3.50e+03, 3.60e+03, 3.70e+03,\n",
       "       3.80e+03, 3.90e+03, 4.00e+03, 4.10e+03, 4.20e+03, 4.30e+03, 4.40e+03,\n",
       "       4.50e+03, 4.60e+03, 4.70e+03, 4.80e+03, 4.90e+03, 5.00e+03, 5.10e+03,\n",
       "       5.20e+03, 5.30e+03, 5.40e+03, 5.50e+03], dtype=float32)\n",
       "Coordinates:\n",
       "  * depth    (depth) float32 0.0 5.0 10.0 15.0 ... 5.3e+03 5.4e+03 5.5e+03\n",
       "Attributes:\n",
       "    standard_name:  depth\n",
       "    bounds:         depth_bnds\n",
       "    positive:       down\n",
       "    units:          meters\n",
       "    axis:           Z</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'depth'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>depth</span>: 102</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a821b86d-331c-486e-b7e5-7350a9605fd5' class='xr-array-in' type='checkbox' checked><label for='section-a821b86d-331c-486e-b7e5-7350a9605fd5' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 5.0 10.0 15.0 20.0 ... 5.1e+03 5.2e+03 5.3e+03 5.4e+03 5.5e+03</span></div><div class='xr-array-data'><pre>array([0.00e+00, 5.00e+00, 1.00e+01, 1.50e+01, 2.00e+01, 2.50e+01, 3.00e+01,\n",
       "       3.50e+01, 4.00e+01, 4.50e+01, 5.00e+01, 5.50e+01, 6.00e+01, 6.50e+01,\n",
       "       7.00e+01, 7.50e+01, 8.00e+01, 8.50e+01, 9.00e+01, 9.50e+01, 1.00e+02,\n",
       "       1.25e+02, 1.50e+02, 1.75e+02, 2.00e+02, 2.25e+02, 2.50e+02, 2.75e+02,\n",
       "       3.00e+02, 3.25e+02, 3.50e+02, 3.75e+02, 4.00e+02, 4.25e+02, 4.50e+02,\n",
       "       4.75e+02, 5.00e+02, 5.50e+02, 6.00e+02, 6.50e+02, 7.00e+02, 7.50e+02,\n",
       "       8.00e+02, 8.50e+02, 9.00e+02, 9.50e+02, 1.00e+03, 1.05e+03, 1.10e+03,\n",
       "       1.15e+03, 1.20e+03, 1.25e+03, 1.30e+03, 1.35e+03, 1.40e+03, 1.45e+03,\n",
       "       1.50e+03, 1.55e+03, 1.60e+03, 1.65e+03, 1.70e+03, 1.75e+03, 1.80e+03,\n",
       "       1.85e+03, 1.90e+03, 1.95e+03, 2.00e+03, 2.10e+03, 2.20e+03, 2.30e+03,\n",
       "       2.40e+03, 2.50e+03, 2.60e+03, 2.70e+03, 2.80e+03, 2.90e+03, 3.00e+03,\n",
       "       3.10e+03, 3.20e+03, 3.30e+03, 3.40e+03, 3.50e+03, 3.60e+03, 3.70e+03,\n",
       "       3.80e+03, 3.90e+03, 4.00e+03, 4.10e+03, 4.20e+03, 4.30e+03, 4.40e+03,\n",
       "       4.50e+03, 4.60e+03, 4.70e+03, 4.80e+03, 4.90e+03, 5.00e+03, 5.10e+03,\n",
       "       5.20e+03, 5.30e+03, 5.40e+03, 5.50e+03], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-1373c4b1-6ab3-491b-b65c-59b5e9a3b44d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1373c4b1-6ab3-491b-b65c-59b5e9a3b44d' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>depth</span></div><div class='xr-var-dims'>(depth)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 5.0 10.0 ... 5.4e+03 5.5e+03</div><input id='attrs-beae6986-a15b-4549-a1b0-7737e0769b78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-beae6986-a15b-4549-a1b0-7737e0769b78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3bc71b6-34f5-47e7-bca5-da3e421ef00b' class='xr-var-data-in' type='checkbox'><label for='data-d3bc71b6-34f5-47e7-bca5-da3e421ef00b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>bounds :</span></dt><dd>depth_bnds</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([0.00e+00, 5.00e+00, 1.00e+01, 1.50e+01, 2.00e+01, 2.50e+01, 3.00e+01,\n",
       "       3.50e+01, 4.00e+01, 4.50e+01, 5.00e+01, 5.50e+01, 6.00e+01, 6.50e+01,\n",
       "       7.00e+01, 7.50e+01, 8.00e+01, 8.50e+01, 9.00e+01, 9.50e+01, 1.00e+02,\n",
       "       1.25e+02, 1.50e+02, 1.75e+02, 2.00e+02, 2.25e+02, 2.50e+02, 2.75e+02,\n",
       "       3.00e+02, 3.25e+02, 3.50e+02, 3.75e+02, 4.00e+02, 4.25e+02, 4.50e+02,\n",
       "       4.75e+02, 5.00e+02, 5.50e+02, 6.00e+02, 6.50e+02, 7.00e+02, 7.50e+02,\n",
       "       8.00e+02, 8.50e+02, 9.00e+02, 9.50e+02, 1.00e+03, 1.05e+03, 1.10e+03,\n",
       "       1.15e+03, 1.20e+03, 1.25e+03, 1.30e+03, 1.35e+03, 1.40e+03, 1.45e+03,\n",
       "       1.50e+03, 1.55e+03, 1.60e+03, 1.65e+03, 1.70e+03, 1.75e+03, 1.80e+03,\n",
       "       1.85e+03, 1.90e+03, 1.95e+03, 2.00e+03, 2.10e+03, 2.20e+03, 2.30e+03,\n",
       "       2.40e+03, 2.50e+03, 2.60e+03, 2.70e+03, 2.80e+03, 2.90e+03, 3.00e+03,\n",
       "       3.10e+03, 3.20e+03, 3.30e+03, 3.40e+03, 3.50e+03, 3.60e+03, 3.70e+03,\n",
       "       3.80e+03, 3.90e+03, 4.00e+03, 4.10e+03, 4.20e+03, 4.30e+03, 4.40e+03,\n",
       "       4.50e+03, 4.60e+03, 4.70e+03, 4.80e+03, 4.90e+03, 5.00e+03, 5.10e+03,\n",
       "       5.20e+03, 5.30e+03, 5.40e+03, 5.50e+03], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b1460d2b-dc92-46cc-813f-98dfbd6de548' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b1460d2b-dc92-46cc-813f-98dfbd6de548' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>bounds :</span></dt><dd>depth_bnds</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'depth' (depth: 102)>\n",
       "array([0.00e+00, 5.00e+00, 1.00e+01, 1.50e+01, 2.00e+01, 2.50e+01, 3.00e+01,\n",
       "       3.50e+01, 4.00e+01, 4.50e+01, 5.00e+01, 5.50e+01, 6.00e+01, 6.50e+01,\n",
       "       7.00e+01, 7.50e+01, 8.00e+01, 8.50e+01, 9.00e+01, 9.50e+01, 1.00e+02,\n",
       "       1.25e+02, 1.50e+02, 1.75e+02, 2.00e+02, 2.25e+02, 2.50e+02, 2.75e+02,\n",
       "       3.00e+02, 3.25e+02, 3.50e+02, 3.75e+02, 4.00e+02, 4.25e+02, 4.50e+02,\n",
       "       4.75e+02, 5.00e+02, 5.50e+02, 6.00e+02, 6.50e+02, 7.00e+02, 7.50e+02,\n",
       "       8.00e+02, 8.50e+02, 9.00e+02, 9.50e+02, 1.00e+03, 1.05e+03, 1.10e+03,\n",
       "       1.15e+03, 1.20e+03, 1.25e+03, 1.30e+03, 1.35e+03, 1.40e+03, 1.45e+03,\n",
       "       1.50e+03, 1.55e+03, 1.60e+03, 1.65e+03, 1.70e+03, 1.75e+03, 1.80e+03,\n",
       "       1.85e+03, 1.90e+03, 1.95e+03, 2.00e+03, 2.10e+03, 2.20e+03, 2.30e+03,\n",
       "       2.40e+03, 2.50e+03, 2.60e+03, 2.70e+03, 2.80e+03, 2.90e+03, 3.00e+03,\n",
       "       3.10e+03, 3.20e+03, 3.30e+03, 3.40e+03, 3.50e+03, 3.60e+03, 3.70e+03,\n",
       "       3.80e+03, 3.90e+03, 4.00e+03, 4.10e+03, 4.20e+03, 4.30e+03, 4.40e+03,\n",
       "       4.50e+03, 4.60e+03, 4.70e+03, 4.80e+03, 4.90e+03, 5.00e+03, 5.10e+03,\n",
       "       5.20e+03, 5.30e+03, 5.40e+03, 5.50e+03], dtype=float32)\n",
       "Coordinates:\n",
       "  * depth    (depth) float32 0.0 5.0 10.0 15.0 ... 5.3e+03 5.4e+03 5.5e+03\n",
       "Attributes:\n",
       "    standard_name:  depth\n",
       "    bounds:         depth_bnds\n",
       "    positive:       down\n",
       "    units:          meters\n",
       "    axis:           Z"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.coords['depth']"
   ]
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  {
   "cell_type": "code",
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       "Frozen({'crs': <xarray.Variable ()>\n",
       "array(-2147483647, dtype=int32)\n",
       "Attributes:\n",
       "    grid_mapping_name:            latitude_longitude\n",
       "    epsg_code:                    EPSG:4326\n",
       "    longitude_of_prime_meridian:  0.0\n",
       "    semi_major_axis:              6378137.0\n",
       "    inverse_flattening:           298.25723, 'lat': <xarray.IndexVariable 'lat' (lat: 180)>\n",
       "array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],\n",
       "      dtype=float32)\n",
       "Attributes:\n",
       "    standard_name:  latitude\n",
       "    long_name:      latitude\n",
       "    units:          degrees_north\n",
       "    axis:           Y\n",
       "    bounds:         lat_bnds, 'lat_bnds': <xarray.Variable (lat: 180, nbounds: 2)>\n",
       "array([[-90., -89.],\n",
       "       [-89., -88.],\n",
       "       [-88., -87.],\n",
       "       ...,\n",
       "       [ 87.,  88.],\n",
       "       [ 88.,  89.],\n",
       "       [ 89.,  90.]], dtype=float32)\n",
       "Attributes:\n",
       "    comment:  latitude bounds, 'lon': <xarray.IndexVariable 'lon' (lon: 360)>\n",
       "array([-179.5, -178.5, -177.5, ...,  177.5,  178.5,  179.5], dtype=float32)\n",
       "Attributes:\n",
       "    standard_name:  longitude\n",
       "    long_name:      longitude\n",
       "    units:          degrees_east\n",
       "    axis:           X\n",
       "    bounds:         lon_bnds, 'lon_bnds': <xarray.Variable (lon: 360, nbounds: 2)>\n",
       "array([[-180., -179.],\n",
       "       [-179., -178.],\n",
       "       [-178., -177.],\n",
       "       ...,\n",
       "       [ 177.,  178.],\n",
       "       [ 178.,  179.],\n",
       "       [ 179.,  180.]], dtype=float32)\n",
       "Attributes:\n",
       "    comment:  longitude bounds, 'depth': <xarray.IndexVariable 'depth' (depth: 102)>\n",
       "array([0.00e+00, 5.00e+00, 1.00e+01, 1.50e+01, 2.00e+01, 2.50e+01, 3.00e+01,\n",
       "       3.50e+01, 4.00e+01, 4.50e+01, 5.00e+01, 5.50e+01, 6.00e+01, 6.50e+01,\n",
       "       7.00e+01, 7.50e+01, 8.00e+01, 8.50e+01, 9.00e+01, 9.50e+01, 1.00e+02,\n",
       "       1.25e+02, 1.50e+02, 1.75e+02, 2.00e+02, 2.25e+02, 2.50e+02, 2.75e+02,\n",
       "       3.00e+02, 3.25e+02, 3.50e+02, 3.75e+02, 4.00e+02, 4.25e+02, 4.50e+02,\n",
       "       4.75e+02, 5.00e+02, 5.50e+02, 6.00e+02, 6.50e+02, 7.00e+02, 7.50e+02,\n",
       "       8.00e+02, 8.50e+02, 9.00e+02, 9.50e+02, 1.00e+03, 1.05e+03, 1.10e+03,\n",
       "       1.15e+03, 1.20e+03, 1.25e+03, 1.30e+03, 1.35e+03, 1.40e+03, 1.45e+03,\n",
       "       1.50e+03, 1.55e+03, 1.60e+03, 1.65e+03, 1.70e+03, 1.75e+03, 1.80e+03,\n",
       "       1.85e+03, 1.90e+03, 1.95e+03, 2.00e+03, 2.10e+03, 2.20e+03, 2.30e+03,\n",
       "       2.40e+03, 2.50e+03, 2.60e+03, 2.70e+03, 2.80e+03, 2.90e+03, 3.00e+03,\n",
       "       3.10e+03, 3.20e+03, 3.30e+03, 3.40e+03, 3.50e+03, 3.60e+03, 3.70e+03,\n",
       "       3.80e+03, 3.90e+03, 4.00e+03, 4.10e+03, 4.20e+03, 4.30e+03, 4.40e+03,\n",
       "       4.50e+03, 4.60e+03, 4.70e+03, 4.80e+03, 4.90e+03, 5.00e+03, 5.10e+03,\n",
       "       5.20e+03, 5.30e+03, 5.40e+03, 5.50e+03], dtype=float32)\n",
       "Attributes:\n",
       "    standard_name:  depth\n",
       "    bounds:         depth_bnds\n",
       "    positive:       down\n",
       "    units:          meters\n",
       "    axis:           Z, 'depth_bnds': <xarray.Variable (depth: 102, nbounds: 2)>\n",
       "array([[0.00e+00, 2.50e+00],\n",
       "       [2.50e+00, 7.50e+00],\n",
       "       [7.50e+00, 1.25e+01],\n",
       "       ...,\n",
       "       [5.25e+03, 5.35e+03],\n",
       "       [5.35e+03, 5.45e+03],\n",
       "       [5.45e+03, 5.50e+03]], dtype=float32)\n",
       "Attributes:\n",
       "    comment:  depth bounds, 'time': <xarray.IndexVariable 'time' (time: 1)>\n",
       "array([8214.], dtype=float32)\n",
       "Attributes:\n",
       "    standard_name:  time\n",
       "    long_name:      time\n",
       "    units:          months since 1900-01-01 00:00:00\n",
       "    axis:           T\n",
       "    climatology:    climatology_bounds, 'climatology_bounds': <xarray.Variable (time: 1, nbounds: 2)>\n",
       "array([[7512., 8928.]], dtype=float32)\n",
       "Attributes:\n",
       "    comment:  This variable defines the bounds of the climatological time per..., 'o_an': <xarray.Variable (time: 1, depth: 102, lat: 180, lon: 360)>\n",
       "[6609600 values with dtype=float32]\n",
       "Attributes:\n",
       "    standard_name:  mole_concentration_of_dissolved_molecular_oxygen_in_sea_w...\n",
       "    long_name:      Objectively analyzed mean fields for mole_concentration_o...\n",
       "    cell_methods:   area: mean depth: mean time: mean within years time: mean...\n",
       "    grid_mapping:   crs\n",
       "    units:          micromoles_per_kilogram, 'o_mn': <xarray.Variable (time: 1, depth: 102, lat: 180, lon: 360)>\n",
       "[6609600 values with dtype=float32]\n",
       "Attributes:\n",
       "    standard_name:  mole_concentration_of_dissolved_molecular_oxygen_in_sea_w...\n",
       "    long_name:      Average of all unflagged interpolated values at each stan...\n",
       "    cell_methods:   area: mean depth: mean time: mean within years time: mean...\n",
       "    grid_mapping:   crs\n",
       "    units:          micromoles_per_kilogram, 'o_dd': <xarray.Variable (time: 1, depth: 102, lat: 180, lon: 360)>\n",
       "[6609600 values with dtype=float64]\n",
       "Attributes:\n",
       "    standard_name:  mole_concentration_of_dissolved_molecular_oxygen_in_sea_w...\n",
       "    long_name:      The number of observations of mole_concentration_of_disso...\n",
       "    cell_methods:   area: sum depth: point time: sum\n",
       "    grid_mapping:   crs\n",
       "    units:          1, 'o_sd': <xarray.Variable (time: 1, depth: 102, lat: 180, lon: 360)>\n",
       "[6609600 values with dtype=float32]\n",
       "Attributes:\n",
       "    long_name:     The standard deviation about the statistical mean of mole_...\n",
       "    cell_methods:  area: mean depth: mean time: standard_deviation\n",
       "    grid_mapping:  crs\n",
       "    units:         micromoles_per_kilogram, 'o_se': <xarray.Variable (time: 1, depth: 102, lat: 180, lon: 360)>\n",
       "[6609600 values with dtype=float32]\n",
       "Attributes:\n",
       "    standard_name:  mole_concentration_of_dissolved_molecular_oxygen_in_sea_w...\n",
       "    long_name:      The standard error about the statistical mean of mole_con...\n",
       "    cell_methods:   area: mean depth: mean time: mean\n",
       "    grid_mapping:   crs\n",
       "    units:          micromoles_per_kilogram, 'o_oa': <xarray.Variable (time: 1, depth: 102, lat: 180, lon: 360)>\n",
       "[6609600 values with dtype=float32]\n",
       "Attributes:\n",
       "    standard_name:  mole_concentration_of_dissolved_molecular_oxygen_in_sea_w...\n",
       "    long_name:      statistical mean value minus the objectively analyzed mea...\n",
       "    cell_methods:   area: mean depth: mean time: mean with years time: mean o...\n",
       "    grid_mapping:   crs\n",
       "    units:          micromoles_per_kilogram, 'o_gp': <xarray.Variable (time: 1, depth: 102, lat: 180, lon: 360)>\n",
       "[6609600 values with dtype=float64]\n",
       "Attributes:\n",
       "    long_name:     The number of grid-squares within the smallest radius of i...\n",
       "    cell_methods:  area: mean depth: mean time: mean within years time: mean ...\n",
       "    grid_mapping:  crs\n",
       "    units:         1})"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "lats = ds.variables['lat'][:]\n",
    "lons = ds.variables['lon'][:]\n",
    "#lats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Use `xarray`'s hooks to `matplotlib` to create a quick-look plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:             (lat: 180, nbounds: 2, lon: 360, time: 1)\n",
       "Coordinates:\n",
       "  * lat                 (lat) float32 -89.5 -88.5 -87.5 -86.5 ... 87.5 88.5 89.5\n",
       "  * lon                 (lon) float32 -179.5 -178.5 -177.5 ... 177.5 178.5 179.5\n",
       "    depth               float32 300.0\n",
       "  * time                (time) float32 8.214e+03\n",
       "Dimensions without coordinates: nbounds\n",
       "Data variables:\n",
       "    crs                 int32 -2147483647\n",
       "    lat_bnds            (lat, nbounds) float32 -90.0 -89.0 -89.0 ... 89.0 90.0\n",
       "    lon_bnds            (lon, nbounds) float32 -180.0 -179.0 ... 179.0 180.0\n",
       "    depth_bnds          (nbounds) float32 287.5 312.5\n",
       "    climatology_bounds  (time, nbounds) float32 7.512e+03 8.928e+03\n",
       "    o_an                (time, lat, lon) float32 nan nan nan ... 299.0 299.0\n",
       "    o_mn                (time, lat, lon) float32 nan nan nan nan ... nan nan nan\n",
       "    o_dd                (time, lat, lon) float64 nan nan nan nan ... 0.0 0.0 0.0\n",
       "    o_sd                (time, lat, lon) float32 nan nan nan nan ... nan nan nan\n",
       "    o_se                (time, lat, lon) float32 nan nan nan nan ... nan nan nan\n",
       "    o_oa                (time, lat, lon) float32 nan nan nan nan ... nan nan nan\n",
       "    o_gp                (time, lat, lon) float64 nan nan nan ... 84.0 83.0 84.0\n",
       "Attributes: (12/49)\n",
       "    Conventions:                     CF-1.6, ACDD-1.3\n",
       "    title:                           World Ocean Atlas 2018 : mole_concentrat...\n",
       "    summary:                         Climatological mean dissolved oxygen for...\n",
       "    references:                      Garcia, H. E., K. Weathers, C. R. Paver,...\n",
       "    institution:                     National Centers for Environmental Infor...\n",
       "    comment:                         global climatology as part of the World ...\n",
       "    ...                              ...\n",
       "    publisher_email:                 NCEI.info@noaa.gov\n",
       "    nodc_template_version:           NODC_NetCDF_Grid_Template_v2.0\n",
       "    license:                         These data are openly available to the p...\n",
       "    metadata_link:                   https://www.nodc.noaa.gov/OC5/woa18/\n",
       "    date_created:                    2019-07-29 \n",
       "    date_modified:                   2019-07-29 </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a3dcefa7-faa9-459b-abd1-7bdf2e038660' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a3dcefa7-faa9-459b-abd1-7bdf2e038660' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 180</li><li><span>nbounds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 360</li><li><span class='xr-has-index'>time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-84720ba2-7c86-45af-aa00-5ea4c4bcb31d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-84720ba2-7c86-45af-aa00-5ea4c4bcb31d' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-37d35d94-d8d8-463d-8a06-6183e5a72e58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37d35d94-d8d8-463d-8a06-6183e5a72e58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afd7bc34-1ac9-4964-beb2-eaf709928545' class='xr-var-data-in' type='checkbox'><label for='data-afd7bc34-1ac9-4964-beb2-eaf709928545' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.5 -178.5 ... 178.5 179.5</div><input id='attrs-3dbbd480-2033-43c9-b3da-7e8fb3253145' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3dbbd480-2033-43c9-b3da-7e8fb3253145' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-beca38db-ca75-4a58-9029-4c7e932f7941' class='xr-var-data-in' type='checkbox'><label for='data-beca38db-ca75-4a58-9029-4c7e932f7941' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-179.5, -178.5, -177.5, ...,  177.5,  178.5,  179.5], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>300.0</div><input id='attrs-6a42ceea-675d-499c-b3ce-07e1b46ad90b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a42ceea-675d-499c-b3ce-07e1b46ad90b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96745a47-10d5-4b89-9a3f-8327f2c40fc8' class='xr-var-data-in' type='checkbox'><label for='data-96745a47-10d5-4b89-9a3f-8327f2c40fc8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>bounds :</span></dt><dd>depth_bnds</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array(300., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.214e+03</div><input id='attrs-bf8eb6ad-29af-426b-bd6d-b869a86d1ed9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf8eb6ad-29af-426b-bd6d-b869a86d1ed9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b90f052-9172-4ce1-8d04-95492171221b' class='xr-var-data-in' type='checkbox'><label for='data-6b90f052-9172-4ce1-8d04-95492171221b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>units :</span></dt><dd>months since 1900-01-01 00:00:00</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>climatology :</span></dt><dd>climatology_bounds</dd></dl></div><div class='xr-var-data'><pre>array([8214.], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fede11bf-9dbf-4f64-b5da-47a592cf321f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fede11bf-9dbf-4f64-b5da-47a592cf321f' class='xr-section-summary' >Data variables: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>-2147483647</div><input id='attrs-533efc0d-6740-4277-b5e9-c586d5cd3fc9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-533efc0d-6740-4277-b5e9-c586d5cd3fc9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55edd98b-354b-49a6-9626-bec9d2ec4c34' class='xr-var-data-in' type='checkbox'><label for='data-55edd98b-354b-49a6-9626-bec9d2ec4c34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>epsg_code :</span></dt><dd>EPSG:4326</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>inverse_flattening :</span></dt><dd>298.25723</dd></dl></div><div class='xr-var-data'><pre>array(-2147483647, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, nbounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-90.0 -89.0 -89.0 ... 89.0 90.0</div><input id='attrs-1d586735-d783-40fa-b3e2-867a3e2155f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d586735-d783-40fa-b3e2-867a3e2155f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e107de4-bd0d-4365-8550-900619ced364' class='xr-var-data-in' type='checkbox'><label for='data-8e107de4-bd0d-4365-8550-900619ced364' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>latitude bounds</dd></dl></div><div class='xr-var-data'><pre>array([[-90., -89.],\n",
       "       [-89., -88.],\n",
       "       [-88., -87.],\n",
       "       ...,\n",
       "       [ 87.,  88.],\n",
       "       [ 88.,  89.],\n",
       "       [ 89.,  90.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -179.0 ... 179.0 180.0</div><input id='attrs-4f07da14-0113-4721-ab78-a039c6c43332' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f07da14-0113-4721-ab78-a039c6c43332' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef56495a-5556-4fc7-8b13-322628174728' class='xr-var-data-in' type='checkbox'><label for='data-ef56495a-5556-4fc7-8b13-322628174728' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>longitude bounds</dd></dl></div><div class='xr-var-data'><pre>array([[-180., -179.],\n",
       "       [-179., -178.],\n",
       "       [-178., -177.],\n",
       "       ...,\n",
       "       [ 177.,  178.],\n",
       "       [ 178.,  179.],\n",
       "       [ 179.,  180.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth_bnds</span></div><div class='xr-var-dims'>(nbounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>287.5 312.5</div><input id='attrs-ccda041a-9689-4339-8f23-17ae1a2f1dfd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccda041a-9689-4339-8f23-17ae1a2f1dfd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7abe9ac-b5d4-4269-a8db-15cb8b2a2891' class='xr-var-data-in' type='checkbox'><label for='data-a7abe9ac-b5d4-4269-a8db-15cb8b2a2891' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>depth bounds</dd></dl></div><div class='xr-var-data'><pre>array([287.5, 312.5], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>climatology_bounds</span></div><div class='xr-var-dims'>(time, nbounds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>7.512e+03 8.928e+03</div><input id='attrs-1b9f441b-87b5-4af2-bdbe-b260b4d99ba9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b9f441b-87b5-4af2-bdbe-b260b4d99ba9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9d9a440-28e8-40b5-bef2-a0898ee2a222' class='xr-var-data-in' type='checkbox'><label for='data-e9d9a440-28e8-40b5-bef2-a0898ee2a222' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>This variable defines the bounds of the climatological time period for each time</dd></dl></div><div class='xr-var-data'><pre>array([[7512., 8928.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_an</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-38458802-857a-4127-b52b-cdc1a185c9cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38458802-857a-4127-b52b-cdc1a185c9cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbe12350-bbd0-4e10-a2dd-e778fd31d3ef' class='xr-var-data-in' type='checkbox'><label for='data-dbe12350-bbd0-4e10-a2dd-e778fd31d3ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mole_concentration_of_dissolved_molecular_oxygen_in_sea_water</dd><dt><span>long_name :</span></dt><dd>Objectively analyzed mean fields for mole_concentration_of_dissolved_molecular_oxygen_in_sea_water at standard depth levels.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: mean within years time: mean over years</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>micromoles_per_kilogram</dd></dl></div><div class='xr-var-data'><pre>array([[[      nan,       nan, ...,       nan,       nan],\n",
       "        [      nan,       nan, ...,       nan,       nan],\n",
       "        ...,\n",
       "        [298.72177, 298.7428 , ..., 298.68393, 298.6995 ],\n",
       "        [299.00278, 299.00278, ..., 299.00278, 299.00278]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_mn</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-546e6d30-1857-428a-a5ea-a00e27cee2f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-546e6d30-1857-428a-a5ea-a00e27cee2f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b979b384-57ba-4a1a-9181-840ab810786c' class='xr-var-data-in' type='checkbox'><label for='data-b979b384-57ba-4a1a-9181-840ab810786c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mole_concentration_of_dissolved_molecular_oxygen_in_sea_water</dd><dt><span>long_name :</span></dt><dd>Average of all unflagged interpolated values at each standard depth level for mole_concentration_of_dissolved_molecular_oxygen_in_sea_water in each grid-square which contain at least one measurement.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: mean within years time: mean over years</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>micromoles_per_kilogram</dd></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan, nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_dd</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-039c9fb4-d598-4fe7-b199-dcd3ad2be1a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-039c9fb4-d598-4fe7-b199-dcd3ad2be1a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-613aa014-ac6c-4c08-8e6a-419401d6c88c' class='xr-var-data-in' type='checkbox'><label for='data-613aa014-ac6c-4c08-8e6a-419401d6c88c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mole_concentration_of_dissolved_molecular_oxygen_in_sea_water number_of_observations</dd><dt><span>long_name :</span></dt><dd>The number of observations of mole_concentration_of_dissolved_molecular_oxygen_in_sea_water in each grid-square at each standard depth level.</dd><dt><span>cell_methods :</span></dt><dd>area: sum depth: point time: sum</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan, nan],\n",
       "        ...,\n",
       "        [ 0.,  0., ...,  0.,  0.],\n",
       "        [ 0.,  0., ...,  0.,  0.]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_sd</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1f4d46d8-81bb-4f87-b31a-6c2231a63877' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f4d46d8-81bb-4f87-b31a-6c2231a63877' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b114a19-f2ec-4dfc-be67-07026d12a7c2' class='xr-var-data-in' type='checkbox'><label for='data-5b114a19-f2ec-4dfc-be67-07026d12a7c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>The standard deviation about the statistical mean of mole_concentration_of_dissolved_molecular_oxygen_in_sea_water in each grid-square at each standard depth level.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: standard_deviation</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>micromoles_per_kilogram</dd></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan, nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_se</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5373fe5d-4d2f-44dc-be49-23f28e95ad63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5373fe5d-4d2f-44dc-be49-23f28e95ad63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6722326a-2ecf-48a0-8243-f4685e1bce34' class='xr-var-data-in' type='checkbox'><label for='data-6722326a-2ecf-48a0-8243-f4685e1bce34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mole_concentration_of_dissolved_molecular_oxygen_in_sea_water standard_error</dd><dt><span>long_name :</span></dt><dd>The standard error about the statistical mean of mole_concentration_of_dissolved_molecular_oxygen_in_sea_water in each grid-square at each standard depth level.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: mean</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>micromoles_per_kilogram</dd></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan, nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_oa</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-434a9bfd-2816-4414-a7ce-b1e1739598a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-434a9bfd-2816-4414-a7ce-b1e1739598a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3879094e-f950-4520-a10e-163c841bc4c1' class='xr-var-data-in' type='checkbox'><label for='data-3879094e-f950-4520-a10e-163c841bc4c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mole_concentration_of_dissolved_molecular_oxygen_in_sea_water</dd><dt><span>long_name :</span></dt><dd>statistical mean value minus the objectively analyzed mean value for mole_concentration_of_dissolved_molecular_oxygen_in_sea_water.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: mean with years time: mean over years</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>micromoles_per_kilogram</dd></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan, nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o_gp</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d87203ad-bcfa-481a-9df0-0631703c6263' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d87203ad-bcfa-481a-9df0-0631703c6263' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1c526a5-16c3-4fa3-af2e-133d0568db17' class='xr-var-data-in' type='checkbox'><label for='data-f1c526a5-16c3-4fa3-af2e-133d0568db17' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>The number of grid-squares within the smallest radius of influence around each grid-square which contain a statistical mean for mole_concentration_of_dissolved_molecular_oxygen_in_sea_water.</dd><dt><span>cell_methods :</span></dt><dd>area: mean depth: mean time: mean within years time: mean over years</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan, nan],\n",
       "        ...,\n",
       "        [80., 78., ..., 79., 78.],\n",
       "        [84., 83., ..., 83., 84.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-361cc698-a8b9-4c3f-973e-04a85457ac2f' class='xr-section-summary-in' type='checkbox'  ><label for='section-361cc698-a8b9-4c3f-973e-04a85457ac2f' class='xr-section-summary' >Attributes: <span>(49)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>title :</span></dt><dd>World Ocean Atlas 2018 : mole_concentration_of_dissolved_molecular_oxygen_in_sea_water Annual  1.00 degree</dd><dt><span>summary :</span></dt><dd>Climatological mean dissolved oxygen for the global ocean from in situ oceanographic profile data</dd><dt><span>references :</span></dt><dd>Garcia, H. E., K. Weathers, C. R. Paver, I. Smolyar, T. P. Boyer, R. A. Locarnini, M. M. Zweng, A. V. Mishonov, O. K. Baranova, D. Seidov, and J. R. Reagan, 2019. World Ocean Atlas 2018, Volume 3: Dissolved Oxygen, Apparent Oxygen Utilization, and Oxygen Saturation.  A. V. Mishonov, Technical Ed., NOAA Atlas NESDIS 83</dd><dt><span>institution :</span></dt><dd>National Centers for Environmental Information (NCEI)</dd><dt><span>comment :</span></dt><dd>global climatology as part of the World Ocean Atlas project</dd><dt><span>id :</span></dt><dd>woa18_all_o00_01.nc</dd><dt><span>naming_authority :</span></dt><dd>gov.noaa.ncei</dd><dt><span>sea_name :</span></dt><dd>World-Wide Distribution</dd><dt><span>time_coverage_start :</span></dt><dd>1900-01-01</dd><dt><span>time_coverage_end :</span></dt><dd>2017-12-31</dd><dt><span>time_coverage_duration :</span></dt><dd>P!!Y</dd><dt><span>time_coverage_resolution :</span></dt><dd>P01Y</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.0</dd><dt><span>geospatial_vertical_min :</span></dt><dd>0.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>5500.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>1.00 degrees</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>1.00 degrees</dd><dt><span>geospatial_vertical_units :</span></dt><dd>m</dd><dt><span>geospatial_vertical_resolution :</span></dt><dd>SPECIAL</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>down</dd><dt><span>creator_name :</span></dt><dd>Ocean Climate Laboratory</dd><dt><span>creator_email :</span></dt><dd>NCEI.info@noaa.gov</dd><dt><span>creator_url :</span></dt><dd>http://www.ncei.noaa.gov</dd><dt><span>creator_type :</span></dt><dd>group</dd><dt><span>creator_institution :</span></dt><dd>National Centers for Environmental Information</dd><dt><span>project :</span></dt><dd>World Ocean Atlas Project</dd><dt><span>processing_level :</span></dt><dd>processed</dd><dt><span>keywords :</span></dt><dd>Oceans&lt; Ocean Oxygen &gt; Dissolved Oxygen</dd><dt><span>keywords_vocabulary :</span></dt><dd>ISO 19115</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table v49</dd><dt><span>contributor_name :</span></dt><dd>Ocean Climate Laboratory</dd><dt><span>contributor_role :</span></dt><dd>Calculation of climatologies</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>publisher_name :</span></dt><dd>National Centers for Environmental Information (NCEI)</dd><dt><span>publisher_institution :</span></dt><dd>National Centers for Environmental Information</dd><dt><span>publisher_type :</span></dt><dd>institution</dd><dt><span>publisher_url :</span></dt><dd>http://www.ncei.noaa.gov/</dd><dt><span>publisher_email :</span></dt><dd>NCEI.info@noaa.gov</dd><dt><span>nodc_template_version :</span></dt><dd>NODC_NetCDF_Grid_Template_v2.0</dd><dt><span>license :</span></dt><dd>These data are openly available to the public. Please acknowledge the use of these data with the text given in the acknowledgment attribute.</dd><dt><span>metadata_link :</span></dt><dd>https://www.nodc.noaa.gov/OC5/woa18/</dd><dt><span>date_created :</span></dt><dd>2019-07-29 </dd><dt><span>date_modified :</span></dt><dd>2019-07-29 </dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:             (lat: 180, nbounds: 2, lon: 360, time: 1)\n",
       "Coordinates:\n",
       "  * lat                 (lat) float32 -89.5 -88.5 -87.5 -86.5 ... 87.5 88.5 89.5\n",
       "  * lon                 (lon) float32 -179.5 -178.5 -177.5 ... 177.5 178.5 179.5\n",
       "    depth               float32 300.0\n",
       "  * time                (time) float32 8.214e+03\n",
       "Dimensions without coordinates: nbounds\n",
       "Data variables:\n",
       "    crs                 int32 -2147483647\n",
       "    lat_bnds            (lat, nbounds) float32 -90.0 -89.0 -89.0 ... 89.0 90.0\n",
       "    lon_bnds            (lon, nbounds) float32 -180.0 -179.0 ... 179.0 180.0\n",
       "    depth_bnds          (nbounds) float32 287.5 312.5\n",
       "    climatology_bounds  (time, nbounds) float32 7.512e+03 8.928e+03\n",
       "    o_an                (time, lat, lon) float32 ...\n",
       "    o_mn                (time, lat, lon) float32 ...\n",
       "    o_dd                (time, lat, lon) float64 ...\n",
       "    o_sd                (time, lat, lon) float32 ...\n",
       "    o_se                (time, lat, lon) float32 ...\n",
       "    o_oa                (time, lat, lon) float32 ...\n",
       "    o_gp                (time, lat, lon) float64 ...\n",
       "Attributes: (12/49)\n",
       "    Conventions:                     CF-1.6, ACDD-1.3\n",
       "    title:                           World Ocean Atlas 2018 : mole_concentrat...\n",
       "    summary:                         Climatological mean dissolved oxygen for...\n",
       "    references:                      Garcia, H. E., K. Weathers, C. R. Paver,...\n",
       "    institution:                     National Centers for Environmental Infor...\n",
       "    comment:                         global climatology as part of the World ...\n",
       "    ...                              ...\n",
       "    publisher_email:                 NCEI.info@noaa.gov\n",
       "    nodc_template_version:           NODC_NetCDF_Grid_Template_v2.0\n",
       "    license:                         These data are openly available to the p...\n",
       "    metadata_link:                   https://www.nodc.noaa.gov/OC5/woa18/\n",
       "    date_created:                    2019-07-29 \n",
       "    date_modified:                   2019-07-29 "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "depth200 = ds.sel(depth='200')\n",
    "depth200\n",
    "\n",
    "depth300 = ds.sel(depth='300')\n",
    "depth300"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "O2_200=depth200['o_an']\n",
    "O2_200\n",
    "\n",
    "O2_300=depth300['o_an']\n",
    "O2_300\n",
    "\n",
    "#ds.drop(dims='time')\n",
    "O2_200=O2_200.squeeze('time')\n",
    "\n",
    "O2_300=O2_300.squeeze('time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "\n",
    "plt.contourf(lons, lats, O2_200, 60,\n",
    "             transform=ccrs.PlateCarree())\n",
    "\n",
    "ax.coastlines()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Colormap normalization\n",
    "\n",
    "- Objects that use colormaps by default linearly map the colors in the colormap from data values vmin to vmax.\n",
    "- [Colormap normalization](https://matplotlib.org/3.1.0/tutorials/colors/colormapnorms.html) provides a means of manipulating the mapping. \n",
    "\n",
    "For instance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.colors as colors\n",
    "norm = colors.Normalize(vmin=-1, vmax=1.)\n",
    "norm(0.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "We can map data to colormaps in a non-linear fashion using other normalizations, for example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.  , 0.25, 0.5 , 0.75, 1.  ])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm = colors.LogNorm(vmin=1e-2, vmax=1e2)\n",
    "np.array(norm([0.01, 0.1, 1., 10., 100.]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### ...back to oxygen\n",
    "Set contour levels to non-uniform intervals and make the colormap centered at the hypoxic threshold using `DivergingNorm`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "levels = [0, 10, 20,  30, 40, 50, 60, 80, 100, 125, 150, 175, 200, 225, \n",
    "          250, 275, 300]\n",
    "\n",
    "norm = colors.TwoSlopeNorm(vmin=levels[0], vmax=levels[-1], vcenter=60.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add a cyclic point to accomodate the periodic domain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cartopy.util import add_cyclic_point\n",
    "field, lon = add_cyclic_point(O2_200, coord=lons)\n",
    "#lat = ds.lat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12, 8))\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "\n",
    "cf = ax.contourf(lons, lats, O2_300, 60,levels=levels, norm=norm, cmap='RdBu',\n",
    "             transform=ccrs.PlateCarree())\n",
    "\n",
    "ax.coastlines()\n",
    "cb = plt.colorbar(cf, shrink=0.5)\n",
    "cb.ax.set_title('μmol m$^{-3}$')\n",
    "ax.set_title('Concentration of Dissolved Oxygen at 300m Depth');\n",
    "plt.savefig('O2_concentrations_300m.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "JGI sample number\n",
       "AMALJGI-DNA-1    -104.416465\n",
       "AMALJGI-DNA-2    -104.416465\n",
       "AMALJGI-DNA-3    -104.416465\n",
       "AMALJGI-DNA-5    -110.711400\n",
       "AMALJGI-DNA-7    -110.711400\n",
       "AMALJGI-DNA-8    -110.711400\n",
       "AMALJGI-DNA-9      64.000000\n",
       "AMALJGI-DNA-10     64.000000\n",
       "AMALJGI-DNA-11     64.000000\n",
       "AMALJGI-DNA-12     64.000000\n",
       "AMALJGI-DNA-13   -105.000000\n",
       "AMALJGI-DNA-14   -105.000000\n",
       "AMALJGI-DNA-15   -105.000000\n",
       "AMALJGI-DNA-18   -102.000000\n",
       "AMALJGI-DNA-17   -102.000000\n",
       "AMALJGI-DNA-19   -102.000000\n",
       "Fuchsman-136     -106.500000\n",
       "Fuchsman-BB2     -107.148000\n",
       "Glass-2          -108.800000\n",
       "Glass-4          -106.300000\n",
       "Glass-6          -104.500000\n",
       "Glass-10         -104.700000\n",
       "Tsementzi        -104.540000\n",
       "Stewart           -70.383333\n",
       "Ganesh            -70.800000\n",
       "Name: longitude, dtype: float64"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas\n",
    "sampling=pandas.read_excel(r'all_ODZ_sampling_information.xlsx', header=2, index_col=0)\n",
    "sample_latitude=sampling.latitude\n",
    "sample_longitude=sampling.longitude\n",
    "sample_latitude\n",
    "sample_longitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12, 8))\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.coastlines(resolution='110m')\n",
    "ax.set_extent([-60, -180, -30, 30], ccrs.PlateCarree())\n",
    "\n",
    "cf = ax.contourf(lons, lats, O2_300, 60,levels=levels, norm=norm, cmap='RdBu',\n",
    "             transform=ccrs.PlateCarree())\n",
    "\n",
    "ax.coastlines()\n",
    "ax.scatter(sample_longitude,sample_latitude,s=65,c='y',edgecolor='black',alpha=1, transform=ccrs.PlateCarree());\n",
    "cb = plt.colorbar(cf, shrink=0.5)\n",
    "cb.ax.set_title('μmol m$^{-3}$')\n",
    "ax.set_title('Concentration of Dissolved Oxygen at 300m Depth');\n",
    "plt.savefig('O2_concentrations_300m_with_sampling_Pacific.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig = plt.figure(figsize=(12, 8))\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.coastlines(resolution='110m')\n",
    "ax.set_extent([-60, -180, -30, 30], ccrs.PlateCarree())\n",
    "\n",
    "cf = ax.contourf(lons, lats, O2_300, 60,levels=levels, norm=norm, cmap='RdBu',\n",
    "             transform=ccrs.PlateCarree())\n",
    "ax.coastlines()\n",
    "\n",
    "colors = {'assembled, MAGs, and mapping':'yellow', 'co-assembled, MAGs, and mapping':'plum', 'mapping':'palegreen'}\n",
    "\n",
    "plot = ax.scatter(sample_longitude,sample_latitude,s=65,c=sampling.assembled.map(colors),\n",
    "           edgecolor='black',alpha=1, transform=ccrs.PlateCarree());\n",
    "cb = plt.colorbar(cf, shrink=0.5)\n",
    "cb.ax.set_title('μmol m$^{-3}$')\n",
    "\n",
    "\n",
    "color_patch = [\"yellow\", \"plum\", \"palegreen\"]\n",
    "texts = [\"assembled, MAGs, and mapping\", \"co-assembled, MAGs, and mapping\",\"mapping\"]\n",
    "patches = [ plt.plot([],[], marker=\"o\", ms=10, ls=\"\", mec=None, color=color_patch[i], \n",
    "            label=\"{:s}\".format(texts[i]) )[0]  for i in range(len(texts)) ]\n",
    "\n",
    "plt.legend(handles=patches, loc='lower left', ncol=1, title=\"Metagenome Usage\",frameon=False,\n",
    "        numpoints=1)\n",
    "\n",
    "ax.set_title('Concentration of Dissolved Oxygen at 300m Depth');\n",
    "plt.savefig('O2_concentrations_300m_with_sampling_Pacific.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig = plt.figure(figsize=(12, 8))\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.coastlines(resolution='110m')\n",
    "#ax.set_extent([-60, -180, -30, 30], ccrs.PlateCarree())\n",
    "\n",
    "cf = ax.contourf(lons, lats, O2_300, 60,levels=levels, norm=norm, cmap='RdBu',\n",
    "             transform=ccrs.PlateCarree())\n",
    "ax.coastlines()\n",
    "\n",
    "colors = {'assembled, MAGs, and mapping':'yellow', 'co-assembled, MAGs, and mapping':'plum', 'mapping':'palegreen'}\n",
    "\n",
    "plot = ax.scatter(sample_longitude,sample_latitude,s=15,c=sampling.assembled.map(colors),\n",
    "           edgecolor='black',alpha=1, transform=ccrs.PlateCarree());\n",
    "cb = plt.colorbar(cf, shrink=0.5)\n",
    "cb.ax.set_title('μmol m$^{-3}$')\n",
    "\n",
    "\n",
    "color_patch = [\"yellow\", \"plum\", \"palegreen\"]\n",
    "texts = [\"assembled, MAGs, and mapping\", \"co-assembled, MAGs, and mapping\",\"mapping\"]\n",
    "patches = [plt.plot([],[], marker=\"o\", ms=10, ls=\"\", mec=None, color=color_patch[i],\n",
    "            label=\"{:s}\".format(texts[i]) )[0]  for i in range(len(texts)) ]\n",
    "\n",
    "plt.legend(handles=patches, loc='lower right', ncol=1, title=\"Metagenome Usage\", \n",
    "           facecolor=\"lightgray\", numpoints=1)\n",
    "\n",
    "ax.set_title('Concentration of Dissolved Oxygen at 300m Depth');\n",
    "plt.savefig('O2_concentrations_300m_with_sampling.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:cartopy]",
   "language": "python",
   "name": "conda-env-cartopy-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
